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Record W2916642183 · doi:10.1039/c9ra00034h

Comparative study of the extrinsic properties of poly(lactic acid)-based biocomposites filled with talc <i>versus</i> sustainable biocarbon

2019· article· en· W2916642183 on OpenAlexafffund
Michael R. Snowdon, Feng Wu, Amar K. Mohanty, Manjusri Misra

Bibliographic record

VenueRSC Advances · 2019
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsDiscovery CentreUniversity of GuelphThornhill Medical (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of Excellence
KeywordsTalcFire retardantLactic acidFiller (materials)Materials scienceComposite materialChemical engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

This study investigates the effects talc and two sizes of biocarbon have as fillers in a PLA bioplastic, when considering them for durable composite applications. Analysis of the PLA-based biocomposites' resistance to wear and flammability accompanied by the vapor barrier characteristics were conducted, with subsequent rheological and thermal properties to further explain the observed results. The compression molded sheets showed a reduction in abrasion by greater than 69% for either filler type compared to the neat PLA due to their high stiffness. In contrast, only the talc provided barrier properties that hindered both water and oxygen permeability, while biocarbon did not possess a high aspect ratio to form a tortuous path necessary for barrier improvement. Yet, the biocarbon-filled PLA biocomposites provided superior flammability resistance due to its char-like caricature that superseded the neat PLA and talc variant which both failed the horizontal burning test. The rheology of the composites provided evidence in the degradation of the PLA chains from the presence of the biocarbon that did not occur with the talc, which may have also contributed to the lower barrier and higher burn resistance from increased dripping. Thus, both talc and biocarbon have their own potential applicability when it comes to acting as a barrier enhancer or flammability retardant due to their intrinsic nature, but both possess wear reinforcement for focus in the tribological area.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.236
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2019
Admission routes2
Has abstractyes

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